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| Section | Weight | Objectives |
|---|---|---|
| Securing AI Systems | 40% | - Security controls for AI systems
|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI-driven threats and risks
|
| AI Governance, Risk and Compliance | 19% | - Governance frameworks and policies
|
| AI-assisted Security | 24% | - Security automation and orchestration
|
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問題 #90
SIMULATION
Instructions
Part1
Use drop-down menu to select the most appropriate protocol or cipher for each system component.
Part2
Use the drop-down menu to select the most appropriate technique to apply to the modified data.
It at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
An engineer is analyzing findings from a penetration test that indicate insufficient data encryption.
The engineer must implement data security.
答案：
解題說明：
Explanation:
Part 1 (Protocols/Ciphers):
API Gateway: TLS 1.2
* Database: AES-512
* AI Model: gRPC
Part 2 (Techniques):
1. {pin:"999-99-9999", name:"john doe"} → {pin:"999-99-9999", name:"john doe", sensitivity:"SECRET"} → Classification
2. {ip_addr:"1.2.3.4", cookie:"aK3idkd==", name:"John Doe" uid="1111"} → {cookie:"aK3idkd==", uid="1111"} → De-identification
3. {pin:"999-99-9999", name:"john doe"} → {pin:"999-99-XXXX", name:"john doe"} → Masking
4. {card_number:"1111222233334444", name:"john doe", user_id:"1"} →
{card_number:"0x019238829", name:"john doe", user_id:"1"} → Tokenization
5. {name:"john doe", patient_id:"10000", dob:"1980-Jan-05"} → {patient_id:"10000", dob:"1980- Jan-05"} → Anonymization Part 1:
* TLS 1.2 secures client-to-gateway communications.
* AES-512 provides strong encryption for data at rest in the database.
* gRPC ensures efficient, secure communication between services (AI model).
Part 2:
* Classification tags sensitive data for handling.
* De-identification strips direct identifiers.
* Masking obscures part of sensitive values while keeping format.
* Tokenization replaces sensitive data with a reversible placeholder.
* Anonymization removes identifying attributes, making re-identification impossible.
問題 #91
An employee wants a consulting company to procure a data set that contains age, ethnicity, and diabetes status. During development, the employer wants to ensure the integrity of the data.
Which of the following is the best strategy to accomplish this task?
答案：D
解題說明：
Basic Concept: Data integrity ensures that data has not been tampered with, corrupted, or modified during storage or transmission. For AI training data that is procured from external sources, cryptographic integrity verification is essential to confirm the data arrived unmodified. CompTIA SecAI+ Study Guide covers data integrity controls for AI data pipelines.
Why A is Correct: Implementing checksums provides cryptographic verification of data integrity. A checksum or hash value such as SHA-256 is computed from the dataset at the source. The receiver computes the same hash and compares it to the provided value. Any modification to the data during transit or storage will produce a different hash, immediately detecting tampering or corruption. This is the most reliable, automated, and scalable strategy for ensuring the integrity of procured training data.
Why B is Wrong: Human evaluation can verify data quality and relevance but is impractical for verifying integrity across large datasets of medical records. Human reviewers cannot detect subtle bit-level corruption or intentional small modifications, and the process is not scalable.
Why C is Wrong: Querying the model tests model performance rather than verifying the integrity of the underlying training data. The model cannot tell you whether its training data was modified after collection or during procurement.
Why D is Wrong: Log monitoring tracks system activities and events over time. While useful for auditing access to data, it cannot retroactively confirm that data content has not been modified and does not provide cryptographic integrity guarantees.
問題 #92
Which of the following types of prompts best describes a developer's input that informs AI interactions?
答案：A
解題說明：
Option A is correct because a system prompt contains the developer- or platform-defined instructions that establish how the AI should behave throughout an interaction. It can define the model's role, objectives, prohibited actions, response style, tool-use boundaries, and security constraints before the user submits a request. That description matches an input supplied by a developer to govern later AI interactions. Option B is the end user's prompt or request; it expresses what the user wants in a particular turn and normally has lower authority than system-level instructions. Option C, zero-shot prompting, describes asking the model to perform a task without providing an example. Option D, multi-shot prompting, supplies multiple examples to demonstrate the desired input or output pattern. Neither zero-shot nor multi-shot identifies the authority or source of the instruction. In a secure AI application, system instructions should be protected from unauthorized modification, tested for conflicts, and reinforced with technical controls rather than treated as the sole security boundary. The essential distinction is prompt hierarchy: system instructions configure persistent behavior, while user prompts request individual tasks.
問題 #93
A recent release of an AI software update exposes confidential customer information due to storage misconfiguration.
Which of the following data security controls will help maintain confidentiality despite the data leak?
答案：C
解題說明：
Basic Concept: When a storage misconfiguration leads to data exposure, the question is which encryption type would have protected the confidentiality of data stored in that misconfigured storage. The three states of data
- at rest, in transit, and in use - each require different encryption mechanisms. CompTIA SecAI+ Study Guide covers encryption states and their applicability to AI data protection.
Why D is Correct: Encryption at rest protects data stored in databases, file systems, and storage media by encrypting it so that even if unauthorized parties gain access to the storage through a misconfiguration, the data remains unreadable without the decryption key. Since the exposure resulted from a storage misconfiguration that allowed access to stored data, encryption at rest would have maintained confidentiality of the customer information despite the misconfiguration granting storage access.
Why A is Wrong: Model encryption specifically protects AI model weights and parameters from unauthorized access. It does not protect customer data stored in databases or data stores associated with the AI system.
Why B is Wrong: Encryption in transit protects data moving between components over networks. It does not protect data stored at rest in misconfigured storage that is accessed directly rather than over a network connection.
Why C is Wrong: Encryption in use (homomorphic encryption or confidential computing) protects data while it is being actively processed in memory. It addresses runtime processing security, not the confidentiality of data stored in misconfigured storage that is not currently being processed.
問題 #94
An IT company implements an adaptable chatbot that learns from user prompts. Based on the conversation shown - where User 2 injected false information about a company acquisition that caused the chatbot to give incorrect responses to User 3 - which of the following compensating controls should an administrator implement to mitigate the issue?
答案：B
解題說明：
Basic Concept: A chatbot that learns from user prompts is vulnerable to data poisoning through conversational injection. Malicious users can deliberately introduce false information that the chatbot incorporates into its knowledge, corrupting responses for subsequent users. CompTIA SecAI+ Study Guide identifies this as a real-time data poisoning vector requiring guardrail controls.
Why D is Correct: Guardrails prevent the chatbot from accepting and incorporating unverified, irrelevant, or potentially malicious information injected by users. They enforce boundaries on what the chatbot can learn from user interactions, validate that information aligns with the system ' s purpose and known facts, and block outputs based on poisoned knowledge. Guardrails are specifically designed to prevent the type of conversational data poisoning demonstrated where a user ' s false claim corrupted the model ' s subsequent responses.
Why A is Wrong: Data encryption protects the confidentiality of data in transit and at rest. It does not prevent a chatbot from accepting and acting on false information that users deliberately inject into the conversation.
Why B is Wrong: API rate limiting restricts the frequency of requests. While it can limit the number of poisoning attempts a single user can make, it does not prevent the chatbot from learning from and propagating false information when requests are made at an acceptable rate.
Why C is Wrong: Transfer learning is a training technique that adapts knowledge from one domain to another.
It is a model development approach, not a runtime control that prevents users from injecting false information into a deployed chatbot.
問題 #95
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